Fashion Demand and Assortment Planning

This application focuses on using data-driven models to decide what fashion products to design, how many to produce, and where and when to stock them. It connects design, merchandising, and inventory planning by forecasting demand at granular levels (style, size, color, store/region) and informing the optimal product mix—known as assortment planning. These systems learn from historical sales, trends, customer behavior, and external signals (e.g., seasonality, events) to reduce guesswork in design and buying decisions. It matters because fashion is highly volatile, with short product lifecycles, strong trend sensitivity, and high risk of overproduction and markdowns. Better demand and assortment planning increases full‑price sell‑through, cuts waste, and supports sustainability goals by aligning production with real demand. It also underpins more personalized shopping experiences, as the right products are available in the right channels, boosting both revenue and customer satisfaction while lowering inventory and operational costs.